base_tablePreview

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses key behaviors: returns top 5 rows, inferred structure, and that the persist parameter materializes a volatile table returning its name. However, it does not explicitly state that the tool is read-only when persist is false, which would aid trust.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: one for purpose and one listing arguments with their semantics. It is front-loaded with the core action, and every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the main functionality and the persist parameter's side effect. However, it does not mention potential errors, performance implications, or the exact return format (e.g., JSON structure). Given no output schema, a bit more detail on the returned data shape would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with parameter descriptions. The description adds value by explicitly stating the default sample size (top 5 rows) and clarifying the persist behavior beyond the schema's minimal description. This slightly exceeds the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'Returns a data sample (top 5 rows) and inferred structure from a database table or view.' This specifies a concrete verb ('Returns'), resource ('database table or view'), and scope ('top 5 rows and inferred structure'), distinguishing it from siblings like base_tableDDL or base_columnDescription.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for quick preview of data and structure but does not explicitly state when to use this tool over alternatives (e.g., base_readQuery for more complex queries). No exclusions or when-not-to-use guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.